Perspectives of Key Court Personnel on the Prosecution of Domestic Violence Cases

Domestic violence (DV) continues to be a public health and criminal justice problem. Several criminal justice system changes have been made to combat DV, such as mandatory arrest policies, no-drop prosecution policies, and specialized DV courts. Perspectives on these policies, DV, and the criminal justice system have been obtained from the victims, police officers, and victim advocates. However, perspectives from those within the criminal justice court system are missing. The purpose of this qualitative phenomenological study was to obtain the perspectives of key court personnel in small rural communities regarding the prosecution of DV cases. Narrative policy framework was used to guide the study. Qualitative semistructured interviews were conducted with two judges, four prosecutors, and three court victim advocates involved in the prosecution of DV cases. The data were analyzed by creating codes, categories, and themes. The category of resources included themes of victims, offenders, and the criminal justice system. Themes of community, criminal justice personnel, and victims were included in the category of education. The common issues with resources that participants noted were the lack of access to childcare, lack of housing, lack of supervised visitation centers, and lack of programming for offenders. Additional education and training for law enforcement, victims, offenders, and the community on the dynamics of DV, why victims recant, and why victims continue to stay with their abusers were recommended by participants. Understanding key court personnel’s perspectives may help change or create better DV policies as they are the people within the system that must enforce such policies resulting in positive social change

Anomalous roughness with system size dependent local roughness exponent

We note that in a system far from equilibrium the interface roughening may depend on the system size which plays the role of control parameter. To detect the size effect on the interface roughness, we study the scaling properties of rough interfaces formed in paper combustion experiments. Using paper sheets of different width \lambda L, we found that the turbulent flame fronts display anomalous multi-scaling characterized by non universal global roughness exponent \alpha and the system size dependent spectrum of local roughness exponents,\xi_q, whereas the burning fronts possess conventional multi-affine scaling. The structure factor of turbulent flame fronts also exhibit unconventional scaling dependence on \lambda These results are expected to apply to a broad range of far from equilibrium systems, when the kinetic energy fluctuations exceed a certain critical value.Comment: 33 pages, 16 figure

Combining machine learning with structurebased protein design to predict and engineer post-Translational modifications of proteins

Post-Translational modifications (PTMs) of proteins play a vital role in their function and stability. These modifications influence protein folding, signaling, protein-protein interactions, enzyme activity, binding affinity, aggregation, degradation, and much more. To date, over 400 types of PTMs have been described, representing chemical diversity well beyond the genetically encoded amino acids. Such modifications pose a challenge to the successful design of proteins, but also represent a major opportunity to diversify the protein engineering toolbox. To this end, we first trained artificial neural networks (ANNs) to predict eighteen of the most abundant PTMs, including protein glycosylation, phosphorylation, methylation, and deamidation. In a second step, these models were implemented inside the computational protein modeling suite Rosetta, which allows flexible combination with existing protocols to model the modified sites and understand their impact on protein stability as well as function. Lastly, we developed a new design protocol that either maximizes or minimizes the predicted probability of a particular site being modified. We find that this combination of ANN prediction and structure-based design can enable the modification of existing, as well as the introduction of novel, PTMs. The potential applications of our work include, but are not limited to, glycan masking of epitopes, strengthening protein-protein interactions through phosphorylation, as well as protecting proteins from deamidation liabilities. These applications are especially important for the design of new protein therapeutics where PTMs can drastically change the therapeutic properties of a protein. Our work adds novel tools to Rosetta s protein engineering toolbox that allow for the rational design of PTMs

Molecular and functional interaction between GPR18 and cannabinoid CB2 G-protein-coupled receptors. Relevance in neurodegenerative diseases

GPR18, still considered an orphan receptor, may respond to endocannabinoids, whose canonical receptors are CB1 and CB2. GPR18 and CB2 receptors share a role in peripheral immune response regulation and are co-expressed in microglia, which are immunocompetent cells in the central nervous system (CNS). We aimed at identifying heteroreceptor complexes formed by GPR18 and CB1R or CB2R in resting and activated microglia. Receptor-receptor interaction was assessed using energy-transfer approaches, and receptor function by determining cAMP levels and ERK1/2 phosphorylation in heterologous cells and primary cultures of microglia. Heteroreceptor identification in primary cultures of microglia was achieved by in situ proximity ligation assays. Energy transfer results showed interaction of GPR18 with CB2R but not with CB1R. CB2-GPR18 heteroreceptor complexes displayed particular functional properties (heteromer prints) often consisting of negative cross-talk (activation of one receptor reduces signaling arising from the partner receptor) and cross-antagonism (the response of one of the receptors is blocked by a selective antagonist of the partner receptor). Activated microglia showed the heteromer print (negative cross-talk and bidirectional cross-antagonism) and increased expression of CB2R and GPR18. Due to the important role of CB2R in neuroprotection, we further investigated heteroreceptor occurrence in primary cultures of microglia from transgenic mice overexpressing human APPSw,Ind, an Alzheimer's disease model. Microglial cells from transgenic mice showed the heteromer print and functional interactions that were similar to those found in cells from wild-type animals that were activated by treatment with lipopolysaccharide and interferon-ɤ. Our results show that GPR18 and its heteromers may play important roles in neurodegenerative processes

Load assessment and analysis of impacts in multibody systems

The evaluation of contact forces during an impact requires the use of continuous force-based methods. An accurate prediction of the impact force demands the identification of the contact parameters on a case-by-case basis. In this paper, the preimpact effective kinetic energy (Formula presented.) is put forward as an indicator of the intensity of the impact force along the contact normal direction. This represents a part of the total kinetic energy of the system that is associated with the subspace of constrained motion defined by the impact constraints at the moment of contact onset. Its value depends only on the mechanical parameters and the configuration of the system. We illustrate in this paper that this indicator can be used to characterize the impact force intensity. The suitability of this indicator is confirmed by numerical simulations and experimentsPostprint (author's final draft

Stability and geometry of silica nano-ribbons (SNRs): a first-principles study

Silica based materials are attractive because of their versatility and their unique structures and properties, which have led to numerous applications of silica in a range of fields. Recently, various low-dimensional silica materials have been synthesized experimentally. Here we present a first-principles study on the geometry and stability of novel low-dimensional silica nano-ribbons (SNRs) using density-functional theory (DFT) with van der Waals interactions (optB88-vdW). SNRs of various widths with different surface groups, and with the geometry of hexagonal rings and squares, were taken into consideration. An atomically flat ribbon with mixing squares and rings is also included. The calculations showed high stability for the single layer and bilayer silica ribbons, both containing hexagonal rings. The calculations also revealed a high flexibility of silica chains. The local structure and chemical bonding were carefully analyzed. Electronic band structure calculations showed an insulating nature of the SNRs with energy gaps of about 5.0 to 6.0 eV, which are determined by nonbonding and anti-bonding O 2p states